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Vision-Based Relative Pose Estimation for Autonomous Rendezvous And Docking
Abstract
Autonomous rendezvous and docking is necessary for planned space programs such as DARPA ASTRO, NASA MSR, ISS assembly and servicing, and other rendezvous and proximity operations. Estimation of the relative pose between the host platform and a resident space object is a critical ability. We present a model-based pose refinement algorithm, part of a suite of algorithms for vision-based relative pose estimation and tracking. Algorithms were tested in high-fidelity simulation and stereo-vision hardware test bed environments. Testing indicated that in most cases, the model-based pose refinement algorithm can handle initial attitude errors up to about 20 degrees, range errors exceeding 10% of range, and transverse errors up to about 2% of range. Preliminary point tests with real camera sequences of a 1/24 scale Magellan satellite model using a simple fixed-gain tracking filter showed potential tracking performance with mean errors of < 3 degrees and < 2% of range.
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“two image simulation tools have so far been specifically developed to support vision-based navigation in space scenes (e.g. Martian surface, asteroid landing): the early PANGU [30] used by ESA and the more comprehensive Airbus internal simulator: SurRender [31], which supports ray tracing and very large datasets.”
From Deep Learning for Spacecraft Pose Estimation from Photorealistic Rendering (2020) · cites this paper as [30]
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“The use of vision-based pose estimation methods in the aerospace area has been previously suggested for autonomous rendezvous and docking [9], satellite navigation [17], on-orbit self-serving [18], and so on.”
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“Relative pose estimation using monocular vision is divided into model-based and model-free approaches [21].”
MethodDecentralized formation pose estimation for spacecraft swarms
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“…that result from using electro-optical sensors in a space environment (Opromolla et al., 2017), there exist various other vision-based relative pose estimation al-26 gorithms (Kelsey et al., 2006; Capuano et al., 2020; Cassinis et al., 2019) implementing application-specific solution strategies.”
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InfluentialPi, J., & Bang, H. (2014) · The Journal of the Astronautical Sciences · doi:10.1007/s40295-014-0016-y · Cited by 17
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Pose Estimation for Non-Cooperative Rendezvous Using Neural Networks
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BackgroundNon-scanning measurement of position and attitude using two linear cameras
Liu, J., Ma, Q., Zhu, H., & Ma, S. (2018) · Optics and Lasers in Engineering · doi:10.1016/j.optlaseng.2018.08.019 · Cited by 5
Guo, D., Wu, S., Weng, D., Gao, C., & Li, W. (2024) · Remote Sensing · doi:10.3390/rs16244690 · Cited by 4
“To address these challenges, computer vision (CV) techniques have been introduced to enhance relative pose estimation between spacecraft [5,6].”
Real-Time Monocular 3-D Pose Tracking for Noncooperative Spacecraft in Close Range
Tang, H., Liu, C., Liu, J., Zhang, P., & Hu, W. (2025) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2025.3568937 · Cited by 4
“…on a single image captured by a passive camera, and in recent decades, it has been widely applied to numerous close-range space missions, such as debris removal, ren-dezvous and docking, and on-orbit servicing [1], [2], [3], [4], [5], owing to its low cost, rapidness, lightweight, and accuracy.”
Vision aided INS for UAV auto landing navigation using SR-UKF based on two-view homography
Cai, M., Xiuxia, S., Song, X., & Liu, X. (2014) · IEEE CSAA Guidance, Navigation and Control Conference (CGNCC) · doi:10.1109/cgncc.2014.7007276 · Cited by 4
“Navigation based on vision is applied to relative navigation due to that auxiliary features (such as surrounding natural environment or artificial marks) are indeed necessary [5-6], e.”
BackgroundAn Information-Theoretic Active Localization Approach during Relative Circumnavigation in Orbit
Kontitsis, M., Panagiotis Tsiotras, B., & Theodorou, E. A. (2016) · AIAA Guidance, Navigation, and Control Conference and Exhibit · doi:10.2514/6.2016-0872 · Cited by 4
Vision-Based Approaches of the Small Satellites Relative Navigation
Erkeç, T. Y., & Hajiyev, C. M. (2021) · WSEAS TRANSACTIONS ON COMPUTER RESEARCH · doi:10.37394/232018.2021.9.3 · Cited by 4
Comparison of EKF&UKF for GNSS Based Micro Satellite Orbital State Estimation
Sever, M., Erkeç, T. Y., & Hajiyev, C. M. (2023) · International Conference on Recent Advances in Space Technologies · doi:10.1109/rast57548.2023.10198010 · Cited by 4
“Guidance, navigation, and control (GNC) are fundamental for making up the satellite's movement estimation structure [5-7].”
BackgroundRelative Pose Estimation under Monocular Vision in Rendezvous and Docking
Pan, H., Huang, J. Y., & Qin, S. Y. (2013) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.433-435.799 · Cited by 4
Non-Cooperative Spacecraft Pose Estimation Using Convolutional Neural Networks
Despond, F. (2021) · doi:10.22215/etd/2021-14867 · Cited by 4
Relative Navigation for the ‘In-Air Capturing’ of a Winged Reusable Launch VehiclePreprint
Singh, S., Luyten, B., & Sagliano, M. (2024) · Research Square · doi:10.21203/rs.3.rs-4674857/v1 · Cited by 4
TAP-Track: Generalizable Spacecraft Pose Tracking by Tracking Any Points
Liu, Y., Qi, Z., Chen, P., Fan, H., Zhu, Y., Yang, J., & Zhang, Y. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3584925 · Cited by 3
“During point (or keypoint) tracking, previous methods such as [10], [11], [13], and [64] often use the architecture of CNN+prediction head, where the CNN extracts image features followed by the prediction head to output the predicted keypoints.”
InfluentialOptimal Pose Estimation with Error-Covariance Analysis
Cheng, Y., & Crassidis, J. L. (2021) · AIAA SciTech Forum · doi:10.2514/6.2021-1758 · Cited by 3
Scale-Consistent Learnable PnP Network for Space Target Pose Estimation
Yang, X., Wang, J., & Duan, S. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3541246 · Cited by 3
“Traditional space target pose estimation typically involves image processing based on manually designed or self-organizing features [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], and prior knowledge of pose [28], [29], [30], [31].”
6-DoF Pose Estimation for Axisymmetric Objects Using Deep Learning with Uncertainty
Hashimoto, S., Hirano, D., & Ishihama, N. (2020) · IEEE Aerospace Conference (AERO) · doi:10.1109/aero47225.2020.9172298 · Cited by 3
“Typical pose estimation methods for spacecraft and space debris are performed using manual template matching, which estimates a suitable pose by minimizing the errors between the detected features in the image and the projected features using a 3D target model [2][3][4].”
MethodVision-Based State Estimation for Non-Cooperative Targets in Space
Bai, C., Guo, J., Wang, L., & Guo, L. (2019) · IEEE International Conference on Unmanned Systems (ICUS) · doi:10.1109/icus48101.2019.8996037 · Cited by 3
“[4] presented a method for predicting pose of the targets in the case of a known 3D model by extracting features, matching projections, and nonlinear optimization.”
MethodAutonomous airborne refueling : relative state estimation
Runhaar, A. J. (2011) · SUNScholar (Stellenbosch University) · Cited by 3
Total Least Squares for Optimal Pose Estimation
Maleki, S., Crassidis, J. L., Cheng, Y., & Schmid, M. (2022) · AIAA SciTech Forum · doi:10.2514/6.2022-1222 · Cited by 2
Space Non-cooperative Target Visual Navigation Fused with Object Detection under Complex Backgrounds
Zhang, S., Wu, A., Ye, Q., Zuo, J., Shao, Y., Shu, L., & Wan, X. (2022) · International Conference on Service Robotics (ICoSR) · doi:10.1109/icosr57188.2022.00035 · Cited by 2
“Instead of PnP, feature-based approaches also include Template Matching (TM) algorithms.”
BackgroundMethodInfluentialAstrobee: Free-Flying Robots for the International Space Station
Smith, T., Alexandrov, O., Barlow, J. S., Benavides, J., Bualat, M. G., Carlino, R., Coltin, B., Cortez, J., Daley, E., Feller, J. R., et al. (2026) · IEEE transactions on field robotics. · doi:10.1109/tfr.2026.3664810 · Cited by 2
Design and development of PROBA-3 rendezvous experiment
Bastante, J. C., Vasconcelos, J. F., Hagenfeldt, M., Peñín, L. F., Dinis, J., & Rebordão, J. M. (2013) · Acta Astronautica · doi:10.1016/j.actaastro.2013.11.018 · Cited by 2
Saliency and Tracking based Semi-supervised Learning for Orbiting Satellite Segmentation
Li, P., Sun, Y., & Wan, X. (2019) · International Conference on Video and Image Processing (ICVIP) · doi:10.1145/3376067.3376103 · Cited by 2
“The visual perception information of the target satellite will help our understanding the state of the satellite for decision making in further step, such as rendezvous and docking [3, 4], repairing and manipulation [5], etc.”
BackgroundUsing Information Features in Computer Vision for 3d Pose Estimation in Space
Melnychuk, S., Gubarev, V. F., & Salnikov, N. N. (2017) · Kibernetika i vyčislitelʹnaâ tehnika · doi:10.15407/kvt190.04.033 · Cited by 2
“Vision-based pose estimation problem was considered in different formulations [2, 3].”
BackgroundThe Effect of Camera Calibration Space on Visual Pose's Precision
Zhou, J., Hao, Y., Zhu, F., & He, L. (2007) · International Conference on Natural Computation (ICNC) · doi:10.1109/icnc.2007.720 · Cited by 2
Metadata
- Authors
- Kelsey, J. M., Byrne, J., Cosgrove, M., Seereeram, S., & Mehra, R. K.
- Affiliations
- Scientific Systems (United States) (US)
- ORCID
- Byrne, J.
- Venue
- 2006 IEEE Aerospace Conference
- Publisher
- IEEE
- Published
- 2006-08-02
- Pages
- 1-20
- ISSN
- 1095-323X (ISSN-L)
- OpenAlex
- W1581087960
- Cited by
- 130
- References
- 21
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 11 · 2023: 12 · 2022: 8 · 2021: 7 · 2020: 12 · 2019: 13 · 2018: 6 · 2017: 4 · 2016: 12 · 2015: 9 · 2014: 8 · 2013: 6 · 2012: 2
- FWCI
- 3.65
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Aerospace Conference (AERO) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Space Satellite Systems and Control
- Physical Sciences › Engineering › Aerospace Engineering › Spacecraft Dynamics and Control
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Keywords
- relative pose estimation, autonomous rendezvous, spacecraft docking, visual object tracking, stereo vision, proximity operations, attitude estimation, range estimation
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